PPT-Email Spam Detection using machine Learning

Lydia Song Lauren Steimle Xiaoxiao Xu Outline Introduction to Project Preprocessing Dimensionality Reduction Brief discussion of different algorithms Knearest D ecision tree Logistic regression. Kallol Dey. Rahul. . Mitra. Shubham. . Gautam. What is Spam ?. According to . wikipedia. … . Email spam, also known as junk email or unsolicited bulk email (UBE),is a subset of electronic spam involving nearly identical messages sent to numerous recipients by email. Clicking on links in spam email may send users to phishing web sites or sites that are hosting malware. . Filtering. Service. Kurt Thomas. , Chris Grier, Justin Ma,. Vern . Paxson. , Dawn Song. University of California, Berkeley. International Computer Science Institute. Motivation. Social Networks. (. Facebook, Twitter). Xiaoxiao. . Xu. , and Dr. Arye Nehorai. Department of Electrical and Systems Engineering, Washington University in St. Louis. Email . has become one of the most important forms of communication. In 2013, there were about 180 billion emails sent per day worldwide and 65% of the emails sent were spam emails. Links in spam emails may lead to users to websites with malware or phishing schemes. Therefore, an effective spam filtering technology is a significant contribution to the sustainability of the cyberspace and to our society.. (Machine Learning). COS 116, Spring . 2012. Adam Finkelstein. Artificial Intelligence. Definition of AI (Merriam-Webster). :. The capability of a machine to imitate intelligent human . behavior. Branch . Zhenhai Duan. Department of Computer Science. Florida State University. Outline. Motivation and background. SPOT algorithm on detecting compromised machines. Performance evaluation . Summary. 2. Motivation. Subvert Your Spam Filter. Blaine Nelson / Marco . Barreno. / . fuching. . Jack Chi / Anthony D. Joseph. Benjamin I. P. Rubinstein / . Udam. . Saini. / Charles Sutton / J.D. . Tygar. / Kai Xia. University of California, Berkeley. Yinzhi Cao. Lehigh University. 1. The reason to forget. Misleading. . worm . signature generators using deliberate noise . injection, in . Proceedings. of the 2006 IEEE Symposium on Security and Privacy, 2006.. Stanford University. Learning. . to improve our lives. Input. Computers Can Learn?. Computers can learn to . predict. Computers can learn to . act. Output. Program. Parameters. Learned to get desired input/output mapping. . 1. Sai Koushik Haddunoori. Problem:. E-mail provides a perfect way to send . millions . of advertisements at no cost for the sender, and this unfortunate fact is nowadays extensively exploited by several . Ethan Grefe. December . 13, . 2013. Motivation. Spam email . is constantly cluttering inboxes. Commonly removed using rule based filters. Spam often has . very similar characteristics . This allows . Massimo . Poesio. INTRO TO MACHINE LEARNING. WHAT IS LEARNING. Memorizing something . Learning facts through observation and exploration . Developing motor and/or cognitive skills through practice . Organizing new knowledge into general, effective representations . Authors. Abu Awal Md Shoeb, Dibya Mukhopadhyay, Shahid Al Noor, Alan Sprague, and Gary Warner. Dec 14, 2014, Harvard University. 1. Introduction. Why spam detection is important. Why it is difficult to detect. Spam is unsolicited . e. mail in the form of:. Commercial advertising. Phishing. Virus-generated . Spam. Scams. E.g. Nigerian Prince who has an inheritance he wishes to share. What is Bulk Email?. Bulk . Yonggang Cui. 1. , Zoe N. Gastelum. 2. , Ray Ren. 1. , Michael R. Smith. 2. , . Yuewei. Lin. 1. , Maikael A. Thomas. 2. , . Shinjae. Yoo. 1. , Warren Stern. 1. 1 . Brookhaven National Laboratory, Upton, USA.